Robust Hash Functions for Digital Watermarking
ITCC '00 Proceedings of the The International Conference on Information Technology: Coding and Computing (ITCC'00)
Perceptual Similarity Metric Resilient to Rotation for Application in Robust Image Hashing
MUE '09 Proceedings of the 2009 Third International Conference on Multimedia and Ubiquitous Engineering
Robust video hashing based on radial projections of key frames
IEEE Transactions on Signal Processing - Part II
Unicity Distance of Robust Image Hashing
IEEE Transactions on Information Forensics and Security - Part 1
Robust and Secure Image Hashing via Non-Negative Matrix Factorizations
IEEE Transactions on Information Forensics and Security - Part 1
Robust and secure image hashing
IEEE Transactions on Information Forensics and Security
Fragile Watermarking With Error-Free Restoration Capability
IEEE Transactions on Multimedia
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
A robust image authentication method distinguishing JPEG compression from malicious manipulation
IEEE Transactions on Circuits and Systems for Video Technology
Perceptual image hashing with histogram of color vector angles
AMT'12 Proceedings of the 8th international conference on Active Media Technology
Fast communication: Robust image hashing using ring-based entropies
Signal Processing
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Structural image features are exploited to construct perceptual image hashes in this work. The image is first preprocessed and divided into overlapped blocks. Correlation between each image block and a reference pattern is calculated. The intermediate hash is obtained from the correlation coefficients. These coefficients are finally mapped to the interval [0, 100], and scrambled to generate the hash sequence. A key component of the hashing method is a specially defined similarity metric to measure the “distance” between hashes. This similarity metric is sensitive to visually unacceptable alterations in small regions of the image, enabling the detection of small area tampering in the image. The hash is robust against content-preserving processing such as JPEG compression, moderate noise contamination, watermark embedding, re-scaling, brightness and contrast adjustment, and low-pass filtering. It has very low collision probability. Experiments are conducted to show performance of the proposed method. (This work was supported by the NSF of China (60773079, 60872116, and 60832010), the High-Tech Res. and Dev. Prog. of China (2007AA01Z477), the Innovative Res. Fdn. of Shanghai Univ. for Ph.D. Programs (shucx080148), and the Sci. Res. Fdn. of Guangxi Normal Univ. for Doctors.)